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Introduction

Helicobacter pylori (H. pylori) is increasingly recognized as a significant pathogen primarily associated with gastrointestinal diseases. While it colonizes the stomach lining, it triggers a systemic immune response, potentially impacting various bodily systems beyond the gastrointestinal tract. This immune response may contribute to the development of diseases in other regions, including ocular conditions.¹

Central Serous Chorioretinopathy (CSCR) is characterized by serous detachment of the neurosensory retina, primarily affecting young men (85% of cases are in males aged 25 to 45). While the acute form is clinically evident, diagnosing CSCR in older patients can be challenging due to similarities with age-related macular degeneration (AMD) and complications like choroidal neovascularization (CNV).^2,3

CSCR causes focal detachments of the neurosensory retina and/or RPE over thickened choroid. It is classified as acute or chronic, with SRD persisting beyond 3–6 months considered chronic. While most cases resolve within this timeframe, up to 50% experience recurrences, multifocal disease, or persistent SRD, leading to potential vision loss.⁴

The relationship between CSCR and corticosteroids is complex. While glucocorticoids can effectively reduce macular edema from various causes, they may paradoxically exacerbate subretinal fluid accumulation in CSCR patients. This highlights the importance of careful management when considering corticosteroid treatment.⁵

The pathophysiology of CSCR is not fully understood, but several risk factors have been identified, including genetics, corticosteroid use, hormonal factors, pregnancy, cardiovascular risk, stress, and obstructive sleep apnea.⁶

Research has also indicated a potential link between H. pylori infection and ocular diseases, including blepharitis, glaucoma, anterior uveitis, and CSCR.⁷

The initial hypothesis linking H. pylori to CSCR was proposed by Sacca, who noted a recurrence in a CSCR patient that correlated with changes in H. pylori test results. Following eradication therapy, significant improvements in retinal structure and visual acuity were observed. Various studies have since investigated this relationship, but findings have been inconsistent.⁸

A 2016 meta-analysis of risk factors for CSC included three studies on the association between CSC and Helicobacter pylori, revealing a significant correlation between the infection and CSC.⁹

This collection of studies highlights the multifactorial nature of both Helicobacter pylori (H. pylori) infection and CSCR, emphasizing the need for further investigation to clarify their potential relationship and implications for ocular health. The proposed association underscores the importance of considering systemic factors in the diagnosis and management of CSCR. The current study is a cross-sectional observational and interventional study design that aims to investigate this association by comparing the prevalence of H. pylori in patients with CSCR to a control group without the condition. Additionally, it will explore correlations between H. pylori infection and various clinical features of CSCR, such as recurrence rates and visual outcomes. By employing a randomized approach, this study seeks to provide more reliable data that enhances understanding of H. pylori’s potential role in the pathogenesis of CSCR and its broader systemic implications.

Materials and Methods

Study Design

This study is a 3-month cross-sectional observational and interventional study, from November 2024 to January 2025, aimed at evaluating the association between H. pylori infection and CSCR. The study also assesses the effect of treatment on visual acuity, and studies the side effects of the treatment regimen.

Study Population

Inclusion Criteria

Inclusion criteria are patients aged 25 to 60 years and the ability to provide informed consent. The study included a total of 80 participants divided into three groups:

Group A

Twenty patients diagnosed with recurrent CSCR episodes.

Group B

Twenty patients diagnosed with CSCR for the first time and not known to have had previous episodes.

Control Group

Forty age- and sex-matched subjects without CSCR.

Exclusion criteria are history of recent ocular surgery or trauma, a known history of gastric surgery or other gastrointestinal disorders affecting H. pylori testing and the current use of corticosteroids or immunosuppressive medications.

Recruitment

Patients diagnosed with CSCR were recruited from Benha university hospitals and Ebsar Eye Center. Control subjects were selected from individuals visiting the two hospitals. Informed consent was obtained from all participants prior to their inclusion in the study.

Data Collection

Clinical data, including demographic information and medical history, were recorded. A comprehensive ophthalmologic examination was performed for all participants, including best-corrected visual acuity (BCVA) measured using Snellen’s chart and converted to LogMAR, fundus examination, fundus fluorescein angiography (FFA) and optical coherence tomography (OCT) including subretinal fluid (SRF) and choroidal neovascularization (CNV) to assess retinal structure and confirm the diagnosis of central serous chorioretinopathy (CSCR).

Optical coherence tomography (OCT) imaging was performed using the Optovue RTVue XR Avanti OCT system (Optovue, Inc., Fremont, CA, USA). The device utilizes a spectral-domain OCT (SD-OCT) technology with a scan speed of 70,000 A-scans per second and a depth resolution of 5 µm. Standardized scanning protocols were applied to assess retinal thickness, choroidal thickness, and the presence of subretinal fluid. All scans were performed under identical lighting conditions and were reviewed for quality assurance to minimize segmentation errors and artifacts.

Diagnosis of H. pylori was confirmed through gut biopsies obtained via UGI endoscopy, followed by histopathological examination and culture, as well as detection of H. pylori antigen in stool using a PCR test. A positive result was defined by the presence of H. pylori antigen in stool and a positive biopsy result.

H. pylori Treatment Regimen

Patients diagnosed with H. pylori infection from the three groups received a 10-day sequential therapy consisting of esomeprazole 40 mg twice daily and amoxicillin 1 g twice daily for the first 5 days, followed by esomeprazole 40 mg twice daily, levofloxacin 500 mg once daily, and tinidazole 500 mg twice daily for the remaining 5 days. Post-treatment visual outcomes were assessed, and any adverse effects related to the therapy were recorded.

Sample Size

The sample size was determined based on an expected prevalence of Helicobacter pylori infection in patients with central serous chorioretinopathy (CSCR) compared to a control population. The minimum required sample size was calculated using the G*Power software. The analysis indicated a minimum of 20 participants per group. A total of 80 participants were enrolled, distributed as follows: 20 in the recurrent CSCR group, 20 in the single-episode CSCR group, and 40 in the control group.

Statistical Analysis

Data were analyzed using the IBBM Statistical Package for the Social Sciences (SPSS). To compare the prevalence of H. pylori infection among the three groups (Group A, Group B, and Control), chi-square tests were employed, with a p-value of <0.05 considered statistically significant. Continuous variables, such as best-corrected visual acuity (BCVA), were analyzed using t-tests or Mann–Whitney U-tests, depending on the distribution of the data. Categorical variables, including recurrence rates, were assessed using chi-square tests or Fisher’s exact tests. Additionally, odds ratios (OR) with 95% confidence intervals (CIs) were calculated to assess the strength of the association between H. pylori infection and CSCR. The overall significance level for all tests was set at p < 0.05.

Results

Demographics

The study enrolled 80 participants, including 20 patients with recurrent Central Serous Chorioretinopathy (CSCR) in Group A, 20 patients with a single episode of CSCR in Group B, and 40 control subjects.

The mean ages were 35 ± 10 years (range: 22–48) for Group A, 38 ± 9 years (range: 26–50) for Group B, and 36 ± 11 years (range: 20–52) for the control group. The gender distribution showed a predominance of males in all groups: 17/3 in Group A, 15/5 in Group B, and 30/10 in the control group. Notably, Group A had an average of 3.5 previous episodes, while Group B had 1.0 (Table 1).

Clinical Features of CSCR

Table 2 presents various clinical features of Central Serous Chorioretinopathy (CSCR) in two groups: those with recurrent episodes (Group A) and those with a single episode (Group B). Group A had significantly more poor outcomes, with a mean best-corrected visual acuity (BCVA) of 0.4 ± 0.2 logMAR compared to 0.2 ± 0.1 logMAR in Group B (p = 0.01). Additionally, Group A exhibited higher rates of retinal pigment epithelium (RPE) detachment (60% vs 30%, p = 0.02) and choroidal neovascularization (40% vs 15%, p = 0.01).

Table 2 Clinical Features of CSCR

Prevalence of H. pylori Infection

Figure 1, Table 3 compares the prevalence of Helicobacter pylori (H. pylori) infection among the three groups. In Group A, 15 out of 20 patients (75%) tested positive for H. pylori, significantly higher than Group B, where 8 out of 20 patients (40%) were positive (p = 0.03, OR = 4.5). The control group showed a 30% prevalence (12 out of 40), with significant differences observed: Group A vs Control (p < 0.001, OR = 7.5) and Group B vs Control (p = 0.02, OR = 1.56). These findings suggest a strong association between H. pylori infection and recurrent CSCR, with a markedly higher odds ratio in Group A, while the association in Group B is moderate.

Table 3 Prevalence of H. pylori Infection Among the Three Groups

Figure 1 Prevalence of H. pylori infection among the three groups.

The analysis highlights a significant association between H. pylori infection and more poor visual outcomes in patients with CSCR. The higher prevalence of subretinal fluid (SRF) in H. pylori-positive patients suggests that infection may exacerbate disease severity. This underscores the potential role of H. pylori in CSCR pathogenesis and the need for targeted management strategies in H. pylori-positive patients (Table 4).

Table 4 Correlation of H. pylori Infection with CSCR Characteristics Across the Three Groups

Figure 2 shows FFA of a case of CSCR and positive for H. pylori.

Figure 2 FFA of a case of CSCR and positive for H. pylori.

Figure 3 shows OCT of the same case of CSCR of Figure 2.

Figure 3 OCT images of the same case of CSCR of Figure 2.

Treatment Regimens for H. pylori Infection

The treatment regimens for Helicobacter pylori (H. pylori) infection were evaluated in different groups. Post-treatment outcomes indicate significant improvements in visual acuity for Groups A and B, while the control group exhibited no significant change. Group A demonstrated a decrease in the mean Best-Corrected Visual Acuity (BCVA) from 0.4 ± 0.2 to 0.3 ± 0.1 (p < 0.001), reflecting a 50% recurrence rate and a 70% improvement in visual symptoms. Similarly, Group B showed a notable improvement, with BCVA improving from 0.3 ± 0.1 to 0.2 ± 0.1 (p = 0.03) and a 10% recurrence rate. In contrast, the control group maintained a stable BCVA (0.2 ± 0.1 both pre- and post-treatment, p = 0.21). These findings highlight the significant impact of treating H. pylori infection on visual acuity outcomes in patients with Central Serous Chorioretinopathy (CSCR), while no such benefit was observed in the control group Figure 4.

Figure 4 Mean BCVA pre & post-treatment of H. pylori infection.

Figure 5 shows 2 weeks post-treatment of H. pylori infection in the same case as Figure 2, OCT showing minimal subretinal fluid.

Figure 5 2 weeks post-treatment of H. pylori Infection of the same case of Figure 2, OCT showing minimal subretinal fluid.

Figure 6 shows 6 weeks post-treatment of H. pylori infection of the same case as Figure 2, OCT showing complete resolution of subretinal fluid.

Figure 6 6 weeks post-treatment of H. pylori infection of the same case of Figure 2, OCT showing complete resolution of subretinal fluid.

Figure 7 summarizes the side effects associated with H. pylori treatment among the three groups: Group A, Group B, and the Control Group. Group A reported the highest prevalence of side effects, with 30% experiencing nausea and 25% suffering from diarrhea, alongside 5% reporting other minor side effects such as abdominal discomfort. Group B showed a slightly lower incidence, with 20% reporting nausea and 15% vomiting, while other side effects occurred in 2% of patients. The Control Group demonstrated a comparable side-effect profile, with 25% reporting nausea, 10% vomiting, and 3% experiencing other minor effects. Statistical analysis revealed no large differences in side effects across the groups, highlighting the need for careful monitoring to ensure patient adherence while managing adverse effects effectively.

Figure 7 Side effects of H. pylori treatment.

Discussion

This study provides valuable insights into the relationship between Helicobacter pylori (H. pylori) infection and Central Serous Chorioretinopathy (CSCR), particularly in distinguishing between recurrent and single-episode cases. The findings suggest a significant association between H. pylori infection and recurrent episodes of CSCR, with 75% of patients in Group A testing positive for the infection compared to 40% in Group B and 30% in the control group.

This aligns with Kanda et al,¹⁰ indicating that systemic factors, including H. pylori, may contribute to ocular conditions, suggesting a multifactorial etiology for CSCR.

Previous studies have also reported a higher prevalence of H. pylori in patients with chronic ocular conditions. For instance, a study by Kocamaz MF et al¹¹ demonstrated that H. pylori infection was significantly associated with various retinal disorders, emphasizing the need to consider systemic infections when evaluating retinal pathologies.

Similarly, a meta-analysis by Gravina AG et al¹² highlighted a potential link between H. pylori and vascular complications, supporting the notion that H. pylori may play a role in the pathogenesis of retinal conditions.

The clinical features observed in this study further emphasize the severity of recurrent CSCR, as evidenced by poorer mean best-corrected visual acuity (BCVA), higher recurrence rates, and increased incidence of retinal pigment epithelium (RPE) detachment and visual disturbances in Group A.

These findings are consistent with prior studies that noted worse visual outcomes in patients with recurrent CSCR episodes, such as the research conducted by Arora et al,¹³ which reported that patients with multiple episodes exhibited significant visual impairment compared to those with single episodes.

In terms of treatment, the high eradication rates of H. pylori achieved in both groups (85% in Group A and 90% in Group B) are comparable to findings from previous studies, such as the work by Wu DW et al,⁷ which reported similar eradication rates using triple and quadruple therapy regimens.

Notably, post-treatment outcomes revealed significant improvements in BCVA and a reduction in recurrence rates, particularly in Group A, which echo findings from Goté et al¹⁴ that demonstrated enhanced visual outcomes following H. pylori eradication in patients with related ocular conditions.

While this study aligns with existing literature, it also highlights the importance of further research to clarify the underlying mechanisms connecting H. pylori to CSCR and to assess the long-term benefits of H. pylori treatment in preventing recurrences. Future studies should explore larger sample sizes and consider additional systemic factors that may influence the pathogenesis of CSCR, as understanding these relationships could enhance clinical management strategies for patients affected by this retinal disorder. Study limitations also include potential patient recall bias.

In conclusion, the findings of this study, supported by previous research, underline the relevance of systemic infections, such as H. pylori, in the context of ocular health and CSCR. This association should also be considered when managing patients with H. pylori infection.

Conclusion

This study establishes a significant association between Helicobacter pylori (H. pylori) infection and Central Serous Chorioretinopathy (CSCR), particularly emphasizing its prevalence in patients experiencing recurrent episodes of the condition. The results demonstrated that patients with recurrent CSCR had a notably higher incidence of H. pylori infection compared to those with a single episode and control subjects. Furthermore, the clinical characteristics of CSCR were significantly more severe in the recurrent group, highlighting the impact of H. pylori on visual acuity, recurrence rates, and associated ocular complications.

The treatment regimens for H. pylori infection in this study achieved high eradication rates, improved visual outcomes, and reduced CSCR recurrence, emphasizing their potential role, particularly in recurrent cases.

Overall, this study highlights the importance of considering systemic factors, such as H. pylori infection, in the diagnosis and treatment of CSCR. Given the implications for ocular health and disease management, further research is warranted to explore the underlying mechanisms linking H. pylori to CSCR and to evaluate the long-term effects of H. pylori treatment on the prevention of CSCR recurrences.

Abbreviations

H. pylori, Helicobacter pylori; CSCR, central serous chorioretinopathy; OCT, Optical coherence tomography; AMD, age-related macular degeneration; CNV, choroidal neovascularization; BCVA, best-corrected visual acuity; FFA, fundus fluorescein angiography; PCR, Polymerase Chain Reaction; SRF, Sub-Retinal Fluid; UGI, Upper Gastrointestinal.

Data Sharing Statement

The data supporting the present findings are contained within the manuscript.

Ethics Approval and Informed Consent

This study was conducted at Benha University Hospital in accordance with the ethical principles outlined in the Declaration of Helsinki. Informed consent was obtained from all participants, and the study protocol was approved by the Institutional Review Board/Ethics Committee. All the patients who participated in the study provided written informed consent.

Consent to Participate

All the patients who participated in the study gave their written consent.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

Authors did not receive any external funding for this work.

Disclosure

The authors declare no competing interests in this work.

References

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2. Zhang X, Lim CZF, Chhablani J, Wong YM. Central serous chorioretinopathy: updates in the pathogenesis, diagnosis and therapeutic strategies. Eye Vis. 2023;10(1):33–66. doi:10.1186/s40662-023-00349-y

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4. Chhablani J, Cohen FB. Multimodal imaging-based central serous chorioretinopathy classification. Ophthalmol Retina. 2020;4(11):1043–1046. doi:10.1016/j.oret.2020.07.026

5. Behar-Cohen F, Zhao M. Mineralocorticoid pathway in retinal health and diseases. Br J Pharmacol. 2022;179(13):3190–3199. doi:10.1111/bph.15770

6. Zarnegar A, Ong J, Matsyaraja T, Arora S, Chhablani J. Pathomechanisms in central serous chorioretinopathy: a recent update. Int J Retina Vitreous. 2023;9(1):3–9. doi:10.1186/s40942-023-00443-2

7. Wu DW, Jiang FP, Ge G, Zhang MX. Association between central serous chorioretinopathy and Helicobacter pylori infection: a systematic review and meta-analysis. Int J Ophthalmol. 2024;17(6):1120–1127. doi:10.18240/ijo.2024.06.18

8. Jain P, Agarwal S, Agrawal A. A clinical trial to study outcome in patients of central serous chorioretinopathy by identification and management of risk factors. J Evol Med Dent Sci. 2019;8(28):2251–2255. doi:10.14260/jemds/2019/493

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MINNEAPOLIS — Roughly half of the patients experience headaches following a hemorrhagic stroke, with more than one third reporting severe pain — yet headache management remains a largely neglected aspect of post-stroke care.

“What we found is that headaches are far more common after hemorrhagic stroke than people might think. For many, the headache lingers even for months-years.” study investigator Bradley Ong, MD, a neurology resident at the Cleveland Clinic in Cleveland, told Medscape Medical News.

Patients often mention headaches while recovering from hemorrhagic stroke, but post-stroke headache tends to not be a focus of care, Ong added.

The findings were presented at American Headache Society (AHS) Annual Meeting 2025.

Knowledge Gap

“So much of stroke research focuses on the acute event, like how to stop the bleeding, and reduce disability, but I kept thinking about what happens after,” said Ong.

Ong added that when he looked into the literature he was “struck by how little we know about post-stroke headaches — particularly following hemorrhagic stroke.” This aspect of the patient experience has been largely overlooked, with surprisingly little research available on post-stroke headaches, particularly following hemorrhagic stroke.

The researchers conducted a systematic review and meta-analysis, identifying 24 studies published through December 2024. The databases included MEDLINE (1964-2024), Embase (1947-2024), and Central (1996-2024).

In all there were data on 4671 individuals who experienced a hemorrhagic stroke and were assessed for acute and chronic post-stroke headache. The majority patients were women (58.2%) living in Europe (70.8%) with a mean age of 56.9 years.

Results showed 47% (95% CI, 39%-87%) developed a headache after a hemorrhagic stroke, with 56% of patients (95% CI, 42%-97%) developing an acute or subacute headache within 30 days post-stroke, and 39% of patients (95% CI, 30%-48%) developing a chronic headache more than 3 months post-stroke. Patients developed severe headache in over one third of cases (36.9%; 95% CI, 14.4%-67.0%), which was defined as a Numeric Rating Scale score ≥ 8.

Among patients who developed post-stroke headache, 48% experienced it following a subarachnoid hemorrhage (SAH), whereas 38% developed it after an intracerebral hemorrhage (ICH).

In both cases, post-stroke headache often progressed to a chronic, persistent condition, with nearly 38% continuing into the chronic phase, the researchers reported.

“In aneurysmal SAH, most headaches had a migrainous phenotype; in contrast, most headaches in ICH had tension-type features, which ranged from moderate to severe in intensity,” the researchers noted.

Little Clinical Guidance

The likelihood of developing a post-stroke headache after a hemorrhagic stroke was influenced by several factors. Male sex was associated with lower odds of headache (pooled odds ratio [OR], 0.82; 95% CI, 0.68-0.99), while a prior history of headache significantly increased the risk (pooled OR, 4.83; 95% CI, 2.10-11.10).

Although the researchers observed considerable heterogeneity among the studies reviewed, the meta-regression analysis showed no statistically significant differences related to the risk of bias, region, population source, or human development index.

Headache does not get the same level of urgency in neurology as other symptoms such as weakness, speech problems, or seizures. “But for patients, these headaches are very real and can be debilitating. We just haven’t done enough to listen to that part of their recovery,” said Ong.

More prospective studies are necessary to improve the understanding of headaches, which frequently receive insufficient attention in research. Ong emphasized that treating headaches in stroke patients is challenging because common over-the-counter medications like nonsteroidal anti-inflammatory drugs are often unsuitable for those who have suffered a brain bleed.

“Long-term follow-up data would also be incredibly valuable, especially since a lot of these patients continue to struggle with headaches well after discharge,” said Ong.

Clinicians should be more intentional in including headache treatment as a part of stroke rehabilitation, he added.

“Right now, there’s very little guidance on how to even define post-stroke headache, and that makes it harder to study and treat. Most of the existing research also comes from a few regions in the world, so we’re missing a truly global picture. We need better, more consistent data from diverse populations to really understand how common this is and what treatments might help,” he added.

More Data Needed

Commenting on the research, Robert G. Kaniecki, MD, founder and director of the UPMC Headache Center in Pittsburgh, noted that the study’s size and scope were strengths. He added that the data are valuable because they specifically focus on patients who have experienced hemorrhagic stroke and subsequently develop headaches.

“Most prior papers have addressed headaches following stroke of any kind — hemorrhagic or the more common ischemic nonhemorrhagic stroke cases,” Kaniecki told Medscape Medical News.

The finding that acute or subacute headache affected 56% of patients was surprising — Kaniecki said he had anticipated a higher rate — while the 39% prevalence of chronic headache was also unexpected, as he had predicted it would be lower.

One limitation in the research was that the studies were mostly published before the third edition of the International Classification of Headache Disorders (ICHD-3) were developed and post-stroke headache was defined with specific criteria, Kaniecki said.

More data on patients with preexisting headaches are also needed, Kaniecki said, and he is interested in knowing how many patients in the study with post-stroke depression ended up developing headaches. “Post-stroke depression is common, and headache a frequent symptom reported by patients with depression,” Kaniecki said.

Ong reported no relevant financial relationships. Kaniecki reported no relevant financial relationships.

Introduction

Gestational diabetes mellitus (GDM) refers to any form of glucose intolerance with onset or first recognition in the perinatal period.¹ Various studies have revealed that GDM could contribute to adverse pregnancy outcomes for both mothers and their offspring. For mothers, GDM patients are at higher risks of subsequent GDM, cardiovascular disease, dysglycemia, and type 2 diabetes.^2–4 For their offspring, GDM could bring out neonatal macrosomia, childhood obesity and metabolic syndrome.⁵ Moreover, the majority of pregnant women who experience GDM are young, which could affect their life for a longer time.

The prevalence of GDM is 1%−28% worldwide, with significant variations observed across different populations.⁶ These differences can be attributed to several factors, including geographic and ethnic predisposition, screening strategies and diagnostic criteria, as well as the varying risk factors.⁷ With improvements in living conditions and strengthened nutrition during pregnancy, the prevalence of GDM is increasing year by year.⁸ Although there are plenty of studies have explored the risk factors of GDM on genetic, lifestyle, diet, and other factors, the pathogenesis of GDM is still unclear. Current studies emphasized placental hormone-driven insulin resistance, β-cell dysfunction, and low-grade inflammation may collectively contribute to GDM development.⁹

Population GDM risk is increasing with the high prevalence of obesity. To provide sufficient energy for fetal growth, blood lipid levels rise as pregnancy progresses.¹⁰ Lipid metabolism is closely related to glycometabolism, which is regulated by insulin. Therefore, dyslipidemia has the potential to induce insulin resistance and the occurrence of GDM. Previous studies have demonstrated the relationships between lipid biomarkers and the risk of GDM. A meta-analysis based on 292 studies interpreted that blood triglyceride (TG) concentrations were significantly different between mothers with GDM and mothers without GDM.¹¹ A few studies showed that elevated serum TG levels and/or decreased high-density lipoprotein cholesterol (HDL−C) could contribute to the development of GDM.^12–16 These studies prompted that TG/HDL−C could be potential indicators of GDM, which is one of the atherogenic indexes.¹⁷

Currently, little information has been given to the risk of GDM derived from atherogenic indices,¹⁸ which were originally calculated to evaluate the risk of atherosclerosis.¹⁹ Notably, another indicator of dyslipidemia of remnant cholesterol, which refers to the cholesterol content within triglyceride-rich lipoprotein remnants (including very-low-density lipoprotein [VLDL], intermediate-density lipoprotein [IDL], and chylomicron remnants), may relate to the occurrence GDM. The connection between remnant cholesterol and the risk of type 2 diabetes has been well-documented, but evidence regarding its role in GDM risk remains insufficient.²⁰ While emerging studies have indicated a positive association between remnant cholesterol and GDM, none have specifically examined the predictive effect of remnant cholesterol on GDM risk.^21–23 Moreover, although dyslipidemia is a potential indicator of GDM as mentioned above, GDM patients might have abnormal atherogenic indices and remnant cholesterol but normal serum lipids at the same time. Therefore, it is still necessary to apply atherogenic indices for the assessment of GDM risk. To fill this gap, this study aimed to investigate the predictive effects of atherogenic indices and remnant cholesterol on the risk of GDM.

Materials and Methods

Study Population

This retrospective study was conducted at the Maternal and Child Health Hospital of Hubei Province, which is one of the largest tertiary hospitals focusing on maternal and child health care in Wuhan City, China. This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Maternal and Child Health Hospital of Hubei Province (2021IECXM005). First, the entire list of inpatients who delivered at this hospital from December 2020 to March 2022 was exported from the clinical information system. Second, patients whose outpatient examination data were complete were reviewed and selected. Complete data were defined as containing the essential independent variables of blood lipid indicators and the outcome variable of GDM diagnosis. There were a total of 6946 inpatients who underwent blood lipid examination in the 1st (0~13⁺⁶ weeks) or 2nd (14~27⁺⁶ weeks) trimester. Third, after removing missing maternal age (essential covariates, N = 26), missing family history of diabetes (essential covariates, N = 33), missing records of in vitro fertilization (IVF) (essential covariates, N = 4), missing body mass index (BMI) (essential covariates, N = 32), multiple pregnancies (have different risk of GDM compared to singleton pregnancies, N = 135), missing oral glucose tolerance test (OGTT) results (outcome measurement, N = 85), and type 1 or type 2 diabetes (pre-gestational dysglycemia confounders, N = 12), 6619 participants were included in this study.

Data Collection

Clinical data were exported from the Hospital’s electronic medical records from the clinical information system. General personal information was collected including maternal age, family history of diabetes (one or more clinically diagnosed diabetes patients within three generations), reproductive history, gestational weight gain, IVF, fasting plasma glucose (FPG) in the 1st trimester of pregnancy, and pre-pregnancy BMI (calculated by self-reported pre-pregnancy weight and height). Specifically, pre-pregnancy BMI was divided into four categories according to the Chinese standard of obesity: underweight (BMI < 18.5), healthy weight (18.5−23.9), overweight (24−27.9), and obese (≥28). Gestational weight gain was classified as insufficient, normal, or excessive according to the standard of recommendation for weight gain during pregnancy released by the Health Industry Standards of the People’s Republic of China.²⁴

Serum lipids, including TG, total cholesterol (TC), HDL−C, and low-density lipoprotein cholesterol (LDL−C) were obtained during the 1st or 2nd trimester of pregnancy. Atherogenic indices including TG/HDL−C, TC/HDL−C, and LDL−C/HDL−C, and remnant cholesterol were regarded as independent variables. All of the independent variables were classified by four interquartile ranges (IQRs).

The dependent variable of GDM was diagnosed according to the recommendations of the International Association of the Diabetes and Pregnancy Study Groups Consensus Panel.²⁵ A 75 g OGTT was performed at 24−28 weeks of gestation on the following criteria: fasting plasma glucose ≥5.1 mmol/L, and/or 1-hour plasma glucose ≥10.0 mmol/L, and/or 2-hour plasma glucose ≥8.5 mmol/L. GDM is diagnosed if one or more of the following glucose values is exceeded.

Data Analysis

The normality of continuous independent variables was examined by Shapiro–Wilk tests. Nonnormal continuous variables were classified into four categories by IQR or summarized as medium (P25, P75). The differences in the prevalence of GDM among subgroups of general personal variables and independent variables were examined by Chi-square tests for categorical variables and Wilcoxon–Mann–Whitney tests for continuous variables. Logistic regression analyses were performed to examine the associations between the independent variables and the risk of GDM. First, the risk of GDM was assessed by several unadjusted logistic regression models for the independent variables, including TC, TG, HDL−C, LDL−C, TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol. The corresponding odds ratios (ORs) and 95% confidence intervals (CIs) were obtained. Second, based on unadjusted logistic regression analysis, the associations between serum lipids and GDM were further adjusted for general personal variables including maternal age, family history of diabetes, parity history, pre-pregnancy BMI, IVF, FPG, and gestational weight gain. To explore the causal relationship between atherogenic indices, remnant cholesterol, and the risk of GDM, stratified analysis of 1st trimester and 2nd trimester were conducted in this study. The normality examinations, Chi-square tests, Wilcoxon–Mann–Whitney tests, and logistic regression analysis were performed with SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Furthermore, the risk of GDM was predicted by nomogram analysis and decision curve analysis (DCA) to gauge the net benefit of identifying high-risk patients that ought to have intervention and the net reduction of unnecessary interventions. The potential nonlinear relationships between the atherogenic indices, remnant cholesterol and the risk of GDM were examined by the restricted cubic splines (RCS). We adopted an RCS with 4 knots, and the media of the atherogenic indices and remnant cholesterols were used as references to obtain the ORs. Nomogram analysis, DCA, and RCS regression analysis were performed with R 4.2.1 (The R Foundation for Statistical Computing, Vienna, Austria). A two-sided P < 0.05 was regarded as statistically significant.

Results

The results showed that the prevalence of GDM was 31.03% (Table 1). Nearly half of the participants were mothers aged 30−34 years (45.34%), and the median age of the participants was 31 years. The prevalence of GDM among the subgroups stratified by age was significantly different (P < 0.0001). Compared with mothers without a family history of diabetes, women with a family history of diabetes had a significantly higher prevalence of GDM (52.58% vs 29.91%, P < 0.0001). Compared with primiparous women, multiparas had a higher prevalence of GDM (34.06% vs 29.53%, P = 0.0002). The prevalence of GDM was higher among mothers who were fertilized by IVF (42.52% vs 30.57%, P < 0.0001). The higher the pre-pregnancy BMI of participants was, the greater the corresponding prevalence of GDM as well (P < 0.0001). Furthermore, the prevalence of GDM was higher among mothers with insufficient gestational weight gain than those with excessive gestational weight gain (52.00% vs 23.42%, P < 0.0001).

The serum atherogenic indices and remnant cholesterols were classified into four categories by IQR, and the differences in the continuity indicators were examined between the GDM group and the control group (Table 2). The prevalence of GDM among the Q4 group in terms of TG/HDL−C, TC/HDL−C, LDL-C/HDL−C, and remnant cholesterol was significantly higher than that among the Q1 group (42.25% vs 23.90%, P < 0.0001; 39.09% vs 23.65%, P < 0.0001; 38.37% vs 23.86%, P < 0.0001; 36.34% vs 24.62%, P < 0.0001; respectively). In line with the Chi-square analysis, the corresponding continuity indicators also showed significant differences between the GDM group and the control group. The results of the univariate analysis between the serum lipid indexes and GDM are provided in Table S1.

Table 2 Atherogenic Indices and Remnant Cholesterol Between Gestational Diabetes Mellitus and Control Group

Table 3 shows the effects of serum atherogenic indices and remnant cholesterol on the risk of GDM. Both adjusted and unadjusted logistic regression analyses presented that atherogenic indices and remnant cholesterol were significantly related to the risk of GDM. Compared to those of the lowest quartile, mothers in the highest quartile of TG/HDL−C had a 66% higher risk of GDM (adjusted OR = 1.66, 95% CI: 1.41, 1.96). Mothers in the highest quartile of TC/HDL−C, LDL-C/HDL−C, and remnant cholesterol demonstrated significantly elevated GDM risk compared to those in the lowest quartile, with adjusted ORs of 1.47 (95% CI: 1.24−1.73), 1.47 (95% CI: 1.24−1.73), and 1.39 (95% CI: 1.18−1.64), respectively. Moreover, Table S2 presented the results of multivariable analysis between serum lipid indexes and GDM stratified by stages of pregnancy. Groups in the highest quartiles of TG, TC, and LDL−C showed higher risks of GDM than did those in the lowest quartile. Furthermore, consistent with Table 3, all atherogenic indices and remnant cholesterol significantly predicted GDM risk stratified by pregnancy stage (Table S3).

Table 3 Multivariable Analysis Between Atherogenic Indices, Remnant Cholesterol and Gestational Diabetes Mellitus

To better visualize the predictive outcomes of TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol, the results of the monogram analyses are provided in Figure 1. The Hosmer and Lemeshow goodness of fit test results for the four groups showed that all of the prediction models were significant (P > 0.05). The AUCs for the TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol predictive models were 0.73 (95% CI: 0.71, 0.74), 0.73 (95% CI: 0.71, 0.74), 0.73 (95% CI: 0.71, 0.74), and 0.72 (95% CI: 0.71, 0.74), respectively. The result of DCA analysis showed that all indicators demonstrated high net benefit (approximately 0.22), excellent sensitivity (>97%), and good negative predictive value (>88%) at a threshold of 0.1 (Figure 2).

Figure 1 The nomogram prediction of gestational diabetes mellitus by atherogenic indices and remnant cholesterol (A) the nomogram prediction of GDM by TG/HDL−C; (B) the nomogram prediction of GDM by TC/HDL−C; (C) the nomogram prediction of GDM by LDL−C/HDL−C; (D) the nomogram prediction of GDM by remnant cholesterol.

Figure 2 The receiver operating characteristic curves and the decision curve analysis of the nomogram predictions (A) the receiver operating characteristic curves of the predictive outcomes of TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol; (B) the decision curve analysis of the predictive outcomes of TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol.

The nonlinear associations between atherogenic indices, remnant cholesterol and GDM are presented in Figure 3. All of the atherogenic indices and remnant cholesterol exhibited unimodal distributions. A nonlinear relationship was detected between atherogenic indices, remnant cholesterol, and the risk of GDM (χ²= 30.91, P < 0.0001; χ²= 13.08, P = 0.0014; χ²= 6.95, P = 0.0309; χ²= 12.52, P = 0.0019; respectively). First, the risk of GDM showed an upward trend with the increasing of TG/HDL−C. But after TG/HDL−C reached 1.64, the risk of GDM started to decline. Similar nonlinear patterns were observed in the relationships between TC/HDL−C, remnant cholesterol, and GDM, with inflection points at 3.47 and 0.65, respectively. Although the LDL−C/HDL−C ratio showed a significant nonlinear relationship with GDM risk, the risk of GDM continued to rise with increasing levels of LDL−C/HDL−C. However, the rising pace decelerated once the ratio exceeded 1.54.

Figure 3 The associations between atherogenic indices and gestational diabetes mellitus risk by RCS regression analysis (A) The associations between TG/HDL−C and GDM; (B) The associations between TC/HDL−C and GDM; (C) The associations between LDL−C /HDL−C and GDM; (D) The associations between remnant cholesterol and GDM. Adjusted for age, pre-pregnancy BMI, gestational weight gain, family history of diabetes, and parity history.

Discussion

The results of this study showed that atherogenic indexes and remnant cholesterol were closely related to the risk of GDM. Higher values of TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol were significantly associated with elevated risks of GDM, and the results of the nomogram analysis showed that these indicators exhibited similar predictive performance, suggesting that all of them may serve as strong predictors for GDM.

In line with this study, previous studies have showed the positive associations between atherogenic indexes and GDM, but little of them examined the predictive ability. A cross-sectional study conducted by Khosrowbeygi et al among Iranian reported that LDL−C/HDL−C, TG/HDL−C, and TC/HDL−C levels were significantly higher in the GDM group than in the control group.¹⁸ Wang et al analyzed data from 15 hospitals in Beijing, China demonstrated that elevated TG/HDL−C and LDL−C/HDL−C in the 1st trimester of pregnancy were related to increased risks of GDM.¹⁷ Pazhohan et al reported that mothers in Iran with the highest tertile of TG/HDL−C in the 1st trimester of pregnancy contributed to a 3.9-fold of the risk of GDM compared with the lowest tertile.²⁶ Cross-sectional studies conducted by Barat et al and Wang et al also revealed that TG/HDL−C was sensitive to GDM diagnosis,^14,27,28 and a retrospective cohort study with a TG/HDL−C ratio cutoff of 3 reported that higher pre-gestational TG/HDL−C was associated with higher rates of GDM (13.1% vs 5.2%).²⁹ Zhang et al conducted a prospective cohort study in the Korean population and suggested that a log10 (TG/HDL) below 0.36 might be beneficial for GDM control.³⁰ Besides, Yue et al investigated serum lipids during the 2nd trimester and found that TG/HDL−C was related to the risk of GDM, but no significant difference was detected for LDL−C/HDL−C.³¹ Liu et al reported that Beijing mothers in the top tertile of TG/HDL−C before 12 weeks’ gestation had a significantly greater risk of GDM (OR = 2.388), but this relationship was not observed in TC/HDL−C.³² Based on the above findings, it was reconfirmed that TG/HDL−C has a positive effect on the risk of GDM, but discrepancies were noted in the relationships between TC/HDL−C and LDL−C/HDL−C and GDM. These gaps could be explained by the different study designs, populations, and gestational weeks of lipid-data collection.

The positive associations between atherogenic indexes and GDM could be explained by insulin resistance regulated by atherogenic indexes. Case-control studies conducted by Xiang et al and Kimm et al aimed to clarify the associations between atherogenic indexes and insulin resistance and revealed that all of the atherogenic indexes were significantly correlated with insulin resistance.^33,34 Specifically, previous studies have confirmed that TG/HDL−C is a reliable biomarker of insulin resistance.^35,36 Moreover, increased TC or decreased HDL−C concentrations could contribute to insulin resistance, glucose intolerance, and hyperinsulinemia,³⁷ and these factors are leading hazards for GDM.

Consistent with our findings, elevated remnant cholesterol levels were significantly associated with an increased risk of GDM. Our study further highlights the promising predictive effect of remnant cholesterol on the risk of GDM. A high concentration of remnant cholesterol was reported to have a higher risk of GDM, even among pregnancies with low TC.²¹ Another prospective cohort study conducted in Korea confirmed the independent association between remnant cholesterol and GDM.²² Su et al reported a significant dose-response relationship that the risk of GDM elevated along with the increasing of remnant cholesterol.²³ Although the exact mechanistic link between remnant cholesterol and GDM remains to be fully elucidated, it was hypothesized that remnant cholesterol may contribute to GDM pathogenesis through dual pathways similar to those observed in type 2 diabetes: The direct effects of remnant cholesterol-induced insulin resistance or β-cell dysfunction,³⁸ and the indirect effects of low-grade inflammation triggered by remnant cholesterol promote insulin resistance.^39,40 Further studies are warranted to validate these mechanisms.

The present study novelly revealed intuitive changes in GDM risk with respect to atherogenic indexes and remnant cholesterol and warned the elevated risk of GDM under high values of atherogenic indexes and remnant cholesterol. However, certain limitations should be addressed. First, the causal correlations between atherogenic indexes and remnant cholesterol and GDM in this study might be undermined. Second, this study obtained clinical data from a single hospital of Chinese population; caution should be taken when generalizing this study to other populations. Third, other confounding factors that might interfere with the relationship between atherogenic indexes and remnant cholesterol and GDM, such as insulin resistance, gestational weight gain before the diagnosis of GDM, liver function indexes, lifestyle behavior factors, and socioeconomic status et al were not considered in this study because they were not routine examined in the clinical practice. Fourth, this study included only one serum lipid data point per person, and the effects of dynamic changes in lipid ratios on the risk of GDM were failed to examine. Future studies focused on the dynamic changes in lipid indicators on the risk of GDM prediction are highly promoted.

Conclusion

Notably, our findings highlight the promising role of atherogenic indices and remnant cholesterol as potential predictive biomarkers for GDM risk assessment, which has not been fully explored in previous studies. Elevated levels of blood TG/HDL−C, TC/HDL−C, LDL−C/HDL−C, and remnant cholesterol are linked to a significant increase in the risk of developing GDM. Therefore, it is essential to maintain atherogenic indexes and remnant cholesterols at low levels in order to reduce the risk of GDM. Specially, the turning points (TG/HDL−C = 1.64, TC/HDL−C = 3.47, LDL−C/HDL−C = 1.54, and remnant cholesterol = 0.65) identified by the nonlinear relationships could serve as potential warning thresholds for clinical interventions to optimize GDM risk assessment. These findings underscore the potential of routine lipid testing as a cost-effective strategy for the early identification and management of GDM in clinical settings.

Abbreviations

GDM, gestational diabetes mellitus; TG, triglyceride; TC, total cholesterol; HDL−C, high-density lipoprotein cholesterol; LDL−C, low-density lipoprotein cholesterol.

Data Sharing Statement

The datasets used during the current study are available from the corresponding author on reasonable request, which should be approved by the Ethics Committee of Maternal and Child Health Hospital of Hubei Province.

Ethics Approval and Informed Consent

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Maternal and Child Health Hospital of Hubei Province (2021IECXM005).

Acknowledgments

We would like to express our gratitude to all obstetric clinical workers in Maternal and Child Health Hospital of Hubei Province for their contributions to the sample accumulation of this paper.

Funding

This study was funded by the Maternal and Child Health Hospital of Hubei Province Research Project [grant No. 2021SFYM007] and Hubei Provincial Natural Science Foundation of China [grant No. 2025AFD690]. All these fundings were received by Dr. Yao Cheng. The funders had no role in the design, data collection, analyses, interpretation, manuscript writing, nor in the decision to publish the results.

Disclosure

The authors report no conflicts of interest in this work.

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